Skip to main content

Table 2 Structure of the educational datasets \(D_i, i = \overline{1,3}\)

From: Extracting topological features to identify at-risk students using machine learning and graph convolutional network models

 

\(F_1\)

\(F_2\)

\(F_3\)

\(\ldots\)

\(F_m\)

Category

\(Student_1\)

\(s_{1,1}\)

\(s_{1,2}\)

\(s_{1,3}\)

\(\ldots\)

\(s_{1,m}\)

\(g_1\)

\(Student_2\)

\(s_{2,1}\)

\(s_{2,2}\)

\(s_{2,3}\)

\(\ldots\)

\(s_{2,m}\)

\(g_2\)

\(Student_3\)

\(s_{3,1}\)

\(s_{3,2}\)

\(s_{3,3}\)

\(\ldots\)

\(s_{3,m}\)

\(g_3\)

\(\vdots\)

\(\vdots\)

\(\vdots\)

\(\vdots\)

\(\ddots\)

\(\vdots\)

\(\vdots\)

\(Student_n\)

\(s_{n,1}\)

\(s_{n,2}\)

\(s_{n,3}\)

\(\ldots\)

\(s_{n,m}\)

\(g_n\)